Better handling of sa_score and qed calculation

docs/source/CHANGELOG.md

@@ -11,17 +11,15 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
-- Calculate SA_score with the molecule without explicit hydrogens. Based on: [https://github.com/rdkit/rdkit/discussions/7047](https://github.com/rdkit/rdkit/discussions/7047)
+- Calculate SA_score with the molecule without explicit hydrogens for all built-in fitness functions. Based on: [https://github.com/rdkit/rdkit/discussions/7047](https://github.com/rdkit/rdkit/discussions/7047)
 
 ### Added
 
 - The `moldrug.constraintconf.clashes_present` function.
-- Attribute `_mol_no_hs` to `moldrug.utils.Inidividual` (the molecule without explicit hydrogens)
 
 ### Changed
 
-- Filtering of conformation that clashes with the protein is no longer with `bio.PDB` object. Now the coordinates are retrieved from the RDKit molecule object and the distance is calculated with NumPy.
-- The `smiles` property of the `moldrug.utils.Inidividual` is obtained from `_mol_no_hs` and not from `mol`
+- `bio.PDB` object is no longer used for filtering of conformations that clash with the protein. Now the coordinates are retrieved from the RDKit molecule object and the distance is calculated with NumPy.
 
 ### Removed
 

src/moldrug/fitness.py

@@ -149,8 +149,6 @@ def __get_mol_cost(mol: Chem.rdchem.Mol,
             update_dict=desirability
         )
 
-    mol_no_hs = Chem.RemoveHs(mol)
-
     if not os.path.exists(wd):
         os.makedirs(wd)
     # Initializing result dict
@@ -160,10 +158,10 @@ def __get_mol_cost(mol: Chem.rdchem.Mol,
     # multicriteria optimization,Optimization of Several Response Variables
 
     # Getting estimate of drug-likness
-    results['qed'] = QED.weights_mean(mol_no_hs)
+    results['qed'] = QED.weights_mean(Chem.RemoveHs(mol))
 
     # Getting synthetic accessibility score
-    results['sa_score'] = sascorer.calculateScore(mol_no_hs)
+    results['sa_score'] = sascorer.calculateScore(Chem.RemoveHs(mol))
 
     # Getting vina_score and update pdbqt
     # Making the ligand pdbqt
@@ -582,10 +580,10 @@ def Cost(
     sascorer = utils.import_sascorer()
     # multicriteria optimization,Optimization of Several Response Variables
     # Getting estimate of drug-likness
-    Individual.qed = QED.weights_mean(Individual._mol_no_hs)
+    Individual.qed = QED.weights_mean(Chem.RemoveHs(Individual.mol))
 
     # Getting synthetic accessibility score
-    Individual.sa_score = sascorer.calculateScore(Individual._mol_no_hs)
+    Individual.sa_score = sascorer.calculateScore(Chem.RemoveHs(Individual.mol))
 
     # Getting vina_score and update pdbqt
     Individual.vina_score, Individual.pdbqt = _vinadock(
@@ -899,10 +897,10 @@ def CostMultiReceptors(
         ad4map = [None] * len(receptor_pdbqt_path)
 
     sascorer = utils.import_sascorer()
-    Individual.qed = QED.weights_mean(Individual._mol_no_hs)
+    Individual.qed = QED.weights_mean(Chem.RemoveHs(Individual.mol))
 
     # Getting synthetic accessibility score
-    Individual.sa_score = sascorer.calculateScore(Individual._mol_no_hs)
+    Individual.sa_score = sascorer.calculateScore(Chem.RemoveHs(Individual.mol))
 
     # Getting Vina score
     pdbqt_list = []

src/moldrug/utils.py

@@ -690,8 +690,6 @@ class Individual:
     ----------
     mol:  Chem.rdchem.Mol
         The molecule object
-    _mol_no_hs: Chem.rdchem.Mol
-        The molecule object without explicit hydrogens.
     idx: Union[int, str]
         The identifier
     pdbqt: str
@@ -748,7 +746,6 @@ def __init__(self, mol: Chem.rdchem.Mol, idx: Union[int, str] = 0, pdbqt: str =
             for the attribute pdbqt on multiple runs. If None, the RNG will not be seeded, by default None
         """
         self.mol = mol
-        self._mol_no_hs = Chem.RemoveHs(self.mol)
 
         if not pdbqt:
             try:
@@ -763,7 +760,7 @@ def __init__(self, mol: Chem.rdchem.Mol, idx: Union[int, str] = 0, pdbqt: str =
 
     @property
     def smiles(self):
-        return Chem.MolToSmiles(self._mol_no_hs)
+        return Chem.MolToSmiles(Chem.RemoveHs(self.mol))
 
     def __repr__(self):
         return f"{self.__class__.__name__}(idx = {self.idx}, smiles = {self.smiles}, cost = {self.cost})"